This disclosure relates to a method of correcting a rotor position sensor signal. The disclosure also relates to a motor control system that utilizes this method, which may be incorporated into a hybrid vehicle.
Electric drive vehicles use electric motors to apply torque to an engine, a driveline, and/or wheels of the vehicle. High efficiency, accurate torque control and functional safety requirements necessitate the use of a position sensor. While resolvers have been historically used for such tasks, an inductive position sensor can be used, which provides sin(θ) and cos(θ) waveforms (“sine and cosine signals”), where θ is the angle of the rotor relative to the stator. Generally speaking, the arctangent operation can be taken to extract the underlying angle. For ideal signals, this will work correctly. Due to manufacturing tolerances in the rotor position sensor's target trace, air gap variation and underlying sensor tolerances, the rotor position sensor sine and cosine signals contain numerous error effects. Such errors can lead to poor position determination and ultimately inaccurate and inefficient motor control.
Existing approaches for improving the angular information from the sensor often require correcting the angle resulting from the processing of the sine and cosine signals, which can be problematic as the errors of the rotor position sensor system are often spectrally close to the desired θ signal. If the error is at known frequencies, then these specific effects can be removed. But, if the effect has a broad spectral content, then it can be extremely challenging to recover the desired rotor position information when removing the error. Furthermore, the overlapping of the θ spectral content and error spectral content can be a function of rotational frequency.
In general, if too much filtering or noise removal is performed, frequency content of θ related to real effects such as acceleration can be lost leading to poor machine control or even precluding the ability to control a machine. Filters or observers can be used but the tradeoff of attempting to track the dynamics of interest while still removing the error is extremely challenging. The challenge is that sufficient position and speed dynamics have to be tracked to keep accurate control of the machine while still removing the error effects that degrade performance.